B.TECH - Semester 7 data mining and information retrieval Question Paper 2013 (dec)
Practice authentic previous year university questions for better exam preparation.
Sample Questions
- With examples compare feature extraction and feature construction.
- Consider the following variable transformations. State the effect of the transformations. (a) $1 / x$
- Consider the following variable transformations. State the effect of the transformations. (b) $|x|$
- Consider the following variable transformations. State the effect of the transformations. (c) standardizing using mean and standard deviation
- Consider the following variable transformations. State the effect of the transformations. (d) standardizing using median and absolute standard deviation
- Describe about SVM classifier.
- Given two objects represented by the tuples $(22,1,42,10)$ and $(20,0,36,8)$ : (a) Compute the Euclidean distance between the two objects.
- Given two objects represented by the tuples $(22,1,42,10)$ and $(20,0,36,8)$ : (b) Compute the Manhattan distance between the two objects.
- Given two objects represented by the tuples $(22,1,42,10)$ and $(20,0,36,8)$ : (c) Compute the Minkowski distance between the two objects, using $q=3$.
- Given two objects represented by the tuples $(22,1,42,10)$ and $(20,0,36,8)$ : (d) Why are the above 3 functions called as distance functions.
- Given a query "what is data mining", how does a search engine retrieve the related documents. （Answer one full question from each module．Each question carries 20 marks） 6．（a）Elaborate on how discretization and binarization are performed． （b）Explain...
- (a) Given the following data, identify the type of the attributes and draw a decision tree to classify a creature as fish, bird, human, cat or horse. | Index | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | | :--- | :---: | :---: | :---: | :---: | :---: | :---: | ...
- (b) Discuss the advantages and disadvantages of using the decision tree classifier with examples. Can a rule based classifier be derived from a decision tree classifier? If so, how?
- (a) Describe the density based clustering algorithms used to discover clusters of arbitrary shape.
- (b) Describe the grid based clustering algorithms with information on how statistical information and wavelet transforms are useful for clustering.
- (a) Compare the various constraint based clustering methods.
- (b) What is model based clustering? Explain the model based clustering techniques.
- (a) Compare spatial and temporal mining.
- (b) Elaborate on how similarity search, classification and prediction analysis of multimedia data performed.
- (a) A database has five transactions. Let min_sup $=60 \%$ and $\min \_$conf $=80 \%$. TID Items bought | T100 | $12,13,14,16,17$ | | :--- | :--- | | T200 | $11,13,15,16,17$ | | T300 | $11,14,19,110$ | | T400 | $11,15,16,19,110$ | | T500 | $13,15,1...